deconvolution_2d.py 文件源码

def backward_cpu(self, inputs, grad_outputs):
        x, V, g = inputs[:3]
        b = inputs[3] if len(inputs) == 4 else None
        if b is None:
            gb = None
            gx, gW = super(Deconvolution2DFunction, self).backward_cpu((x, self.W), grad_outputs)
        else:
            gx, gW, gb = super(Deconvolution2DFunction, self).backward_cpu((x, self.W, b), grad_outputs)

        xp = cuda.get_array_module(x)
        gg = xp.sum(gW * self.normalizedV, axis=(0, 2, 3), keepdims=True).astype(g.dtype, copy=False)
        gV = g * (gW - gg * self.normalizedV) / self.normV
        gV = gV.astype(V.dtype, copy=False)

        if b is None:
            return gx, gV, gg
        else:
            return gx, gV, gg, gb